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Found 8 papers, 1 papers with code
Design and Development of a Lorentz Force-Based MRI-Driven Neuroendoscope
The integration of magnetic resonance imaging (MRI)-driven surgical devices with intraoperative imaging and endoscopy can enable further advancements in surgical treatments and outcomes.
Unsupervised Odometry and Depth Learning for Endoscopic Capsule Robots
In the last decade, many medical companies and research groups have tried to convert passive capsule endoscopes as an emerging and minimally invasive diagnostic technology into actively steerable endoscopic capsule robots which will provide more intuitive disease detection, targeted drug delivery and biopsy-like operations in the gastrointestinal(GI) tract.
Robotics
Sparse-then-Dense Alignment based 3D Map Reconstruction Method for Endoscopic Capsule Robots
Since the development of capsule endoscopcy technology, substantial progress were made in converting passive capsule endoscopes to robotic active capsule endoscopes which can be controlled by the doctor.
Deep EndoVO: A Recurrent Convolutional Neural Network (RCNN) based Visual Odometry Approach for Endoscopic Capsule Robots
Ingestible wireless capsule endoscopy is an emerging minimally invasive diagnostic technology for inspection of the GI tract and diagnosis of a wide range of diseases and pathologies.
A fully dense and globally consistent 3D map reconstruction approach for GI tract to enhance therapeutic relevance of the endoscopic capsule robot
In the gastrointestinal (GI) tract endoscopy field, ingestible wireless capsule endoscopy is emerging as a novel, minimally invasive diagnostic technology for inspection of the GI tract and diagnosis of a wide range of diseases and pathologies.
Magnetic-Visual Sensor Fusion based Medical SLAM for Endoscopic Capsule Robot
A reliable, real-time simultaneous localization and mapping (SLAM) method is crucial for the navigation of actively controlled capsule endoscopy robots.
A Deep Learning Based 6 Degree-of-Freedom Localization Method for Endoscopic Capsule Robots
We present a robust deep learning based 6 degrees-of-freedom (DoF) localization system for endoscopic capsule robots.
A Non-Rigid Map Fusion-Based RGB-Depth SLAM Method for Endoscopic Capsule Robots
In this paper, we propose to our knowledge for the first time in literature a visual simultaneous localization and mapping (SLAM) method specifically developed for endoscopic capsule robots.
